Prediction Of Heart Disease Using Back Propagation MLP Algorithm
Durairaj M, Revathi V
Index Terms: Minimum ECG, MRI, MLP, Nerual Network.
Abstract: Diagnosing the presence of heart disease is actually tedious process,as it requires depth knowledge and rich experience. In general, the prediction of heart disease lies upon the traditional way of examining medical report such as ECG (The Electrocardiogram), MRI (Magnetic Resonance Imaging), Blood Pressure, Stress tests by a medical practitioner. Now days, a large volume of medical data is available in medical industry and acts as a great source of predicting useful and hidden facts in almost all medical problems. These facts would really in turn, help the practitioners to make accurate predictions. The novel techniques of Artificial Neural Network concepts have also been contributing themselves in yielding highest prediction accuracy over medical data. This paper aims to predict the existence of heart disease using Back Propagation MLP (Multilayer Perceptron) of Artificial Nerual Network. The results are compared with the existing works carried out in the same domain.
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